code: def train(
      self,
      input_filepath: str,
      args: TrainArgs,
      eval_filepath: str = "",
  ):
      if type(args) == dict:
          raise ValueError(
              "Dictionary training arguments are no longer supported as of Happy Transformer version 3.0.0."
          )
  
      if args.eval_ratio <= 0 and eval_filepath == "":
          raise ValueError(
              "Please set TrainArgs.eval_ratio to greater than 0  or supply an eval_path"
          )
  
      train_tok_data, eval_tok_data = self._preprocess_data_train(
          input_filepath=input_filepath,
          eval_filepath=eval_filepath,
          args=args,
      )
  
      self._run_train(
          train_tok_data, eval_tok_data, args, self._data_collator
      )
  
imports: import logging
  import os
  import tempfile
  from typing import Union
  from datasets import Dataset, DatasetDict, load_dataset, load_from_disk
  import torch
  from transformers import AutoConfig, AutoModel, AutoTokenizer, Seq2SeqTrainer, Seq2SeqTrainingArguments, Trainer, TrainingArguments
  from happytransformer.args import EvalArgs, TrainArgs
  from happytransformer.fine_tuning_util import EvalResult, FistStep, ZERO_2_SETTINGS, ZERO_3_SETTINGS
label_desc: Use image node_id 6 for calling the HappyTransformer obj's underlying member method code with example usage: obj.train(input_filepath, args, eval_filepath) without return types